In recent years, with the trend of applying deep learning (DL) in high performance scientific
computing, the unique characteristics of emerging DL workloads in HPC raise great …

Distributed cloud/edge (DCE) platform has become popular in recent years. This paper
proposes a new AI benchmark suite for assessing the performance of DCE platforms in …

Edge computing has become popular in the last decade and will advance in future to
support real-time actionable analytics at the devices. One of the fundamental problems for …

Earlier-stage evaluations of a new AI architecture/system need affordable AI benchmarks.
Only using a few AI component benchmarks like MLPerf alone in the other stages may lead …

Artificial Intelligence (AI) technology has been empowered to be a significant driven force
within the edge context for powering up contemporary complex systems, such as smart …

AI benchmarking provides yardsticks for benchmarking, measuring and evaluating
innovative AI algorithms, architecture, and systems. Coordinated by BenchCouncil, this …

Federated learning is a new machine learning paradigm. The goal is to build a machine
learning model from the data sets distributed on multiple devices–so-called an isolated data …

Abstract 2D Face recognition has been extensively studied for decades and has reached
remarkable results in recent years. However, 2D Face recognition is sensitive to variations in …

With the rise of the Internet of Things (IoT), there is a demand for computation at network
edges because of the limited processing capacity of IoT devices. Fog computing is a middle …

Novel Artificial Intelligence (AI) approaches try to process an excessive amount of field-level
data. However, challenges arise as network bandwidth is limited, and thus this data cannot …